Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping

Modal parameter identification is an important content for the research on dynamic behavior of civil engineering structures. For the conventional modal parameter identification techniques, excitation signal and response signal are necessary. But excitations can not be measured for structures under natural loading conditions, or excited by random forces. So, the operational modal parameter identification approaches are developing to identify structural modal parameters by using vibration response signal directly. In this paper, a new method for modal parameter identification depending on ambient excitation response signal is proposed based on independent component analysis (ICA). For modal coordinates independent of each other, ICA can extract modal coordinates of structure and estimate mode shape matrix using vibration response signal directly. The free vibration responses can be obtained by random decrement technique (RDT) from modal coordinates which are random processes, and then the natural frequencies and damping ratios are calculated by Hilbert transform. Numerical simulation results indicate that this method is effective and suitable for output-only structural modal parameter identification.

In this study, an output-only modal identification approach is proposed for decentralized wireless sensor nodes used for linear structural systems. The following approaches are implemented to achieve the objective. Firstly, an output-only modal identification method is selected for decentralized wireless sensor networks. Secondly, the effect of time-unsynchronization is assessed with respect to the accuracy of modal identification analysis. Time-unsynchronized signals are analytically examined to quantify uncertainties and their corresponding errors in modal identification results. Thirdly, a modified approach using complex mode shapes is proposed to reduce the unsynchronization-induced errors in modal identification. In the new way, complex mode shapes are extracted from unsynchronized signals to deal both with modal amplitudes and with phase angles. Finally, the feasibility of the proposed approach is evaluated from numerical and experimental tests by comparing with the performance of existing approach using real mode shapes.

Particle filtering with adaptive resampling scheme for modal frequency identification and dispersion curves estimation in ocean acoustics

The ancient masonry city hall in L'Aquila, Italy (Margherita Palace) that was severely damaged during the L'Aquila earthquake in April 2009 has been subjected to ambient vibration tests to determine its dynamic characteristics such as the natural frequencies, mode shapes, and damping ratios. The processing of ambient vibration responses is performed with three output-only identification approaches: (1) the frequency-domain decomposition, (2) random decrement (RD) technique combined with the eigensystem realization algorithm (ERA), and (3) the natural excitation technique (NExT) combined with ERA. Measurements were made in the palace and in the civic tower using 15 sensors in three different configurations, and the ambient vibration tests involved the simultaneous measurements of longitudinal and lateral vibrations. Lateral vibration modes for the civic tower were identified clearly; a total of five modal shapes and frequencies were identified in the frequency range 0 to 7 Hz. The modal identification in the palace was more difficult because of the severe damage; however, the two bending modes in the perpendicular directions were identified. The comparison of the three experimental techniques shows good agreement, confirming the reliability of the three identification methods. The results of the modal identification have been used to update the finite-element model of the palace. DOI: 10.1061/(ASCE)ST.1943-541X.0000494. © 2012 American Society of Civil Engineers. CE Database subject headings: Historic buildings; Masonry; Finite element method; Vibration; Structural analysis; Earthquakes; Italy. Author keywords: Output-only modal identification; Frequency domain decomposition (FDD); Eigensystem realization algorithm (ERA); Random decrement (RD); Masonry structure; Finite-element model; Ambient vibration; Identification; EMA; Operational modal analysis.

This study aims to improve the accuracy of the parametric estimation of systems with modal interference in the frequency domain. The theory of modal identification states that the frequency response function can be expressed as a rational function form by using the curve fitting technique, and the modal parameters can then be estimated from rational fractional coefficients. The conventional common denominator model only indicates the frequency response function of a single-degree-of-freedom system; thus, it cannot acquire the mode shape information. In this paper, we propose the matrix-fractional coefficient model constructed by the frequency response functions of a multiple-degree-of-freedom system for modal identification. To avoid the phenomenon of omitted modes caused by the distortion from modal interference among the vibration modes of systems during modal estimation, we use a system model with higher-order matrix-fractional coefficients, but fictitious modes may be caused by numerical computation. Structural and fictitious modes can be effectively separated by using a different-order constructed stabilization diagram. Modal identification can be implemented by solving the eigenproblem of the companion matrix yielded from least-square estimation. Numerical simulations, including a full model of sedan and one-half railway vehicle in the form of a linear 2D model, as well as the experimental testing of an actual plate, confirm the validity and robustness of the proposed parametric-estimation method for a system with modal interference under noisy conditions.

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an nth order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a 3rd order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

Considerable efforts have been made towards the development of robust and fully automated vibration-based monitoring systems with the goal of extracting relevant information regarding the dynamic behaviour and health condition of the monitored structure. Satisfactory results have been obtained in this scientific domain by combining accurate measurement systems and fully automated output-only modal identification techniques. In this context, the main objective of this contribution is to demonstrate in a full-scale case study that with the application of sophisticated algorithms for the automatic tracking of modal parameters, it is possible to detect very small structural changes. Apart from describing the main features and capabilities of the autonomous monitoring system implemented to assess the structural condition of a peculiar football stadium suspension roof, this paper also outlines the main results obtained over the course of 4 years of monitoring carried out to assess the dynamic behaviour and the health condition of the roof structure. The routines developed for the online processing of the continuously collected acceleration time series include state-of-the-art processing techniques, such as automated modal identification based on cluster analysis and principal components analyses combined with control charts for removal of environmental or operational effects and detection of structural changes, together with some innovative features in the context of continuous dynamic monitoring, such as the quantification of the uncertainties associated with each modal estimate and the estimation of the contribution of each mode to the measured structural response.

ABSTRACTDevelopment of video‐based vibration techniques and reliability of displacement measurements have important implications in several areas, including structural testing and monitoring of large structures. Through the use of numerous targets placed on the structure, 3‐dimensional (3D) analysis, and modal identification can be performed with minimal installation costs, no mass increase, and contactlessly. This study applies and validates video tracking of targets for vibration analysis of a large‐scale structure, namely, a reinforced concrete U‐shaped wall, tested experimentally under seismic excitation on a shake table. 2D grids of targets are placed on two orthogonal surfaces and filmed by several cameras. Values obtained from a motion capture system, digital image correlation, and traditional displacement sensors are compared. Results confirm that the 3D motion of the U‐shaped wall surfaces and foundation can be accurately extracted from video analysis.

The paper summarizes the dynamic-based assessment of a reinforced concrete arch bridge, dating back to the 50`s. The outlined approach is based on ambient vibration testing, output-only modal identification and updating of the uncertain structural parameters of a finite element model. The Peak Picking and the Enhanced Frequency Domain Decomposition techniques were used to extract the modal parameters from ambient vibration data and a very good agreement in both identified frequencies and mode shapes has been found between the two techniques. In the theoretical study, vibration modes were determined using a 3D Finite Element model of the bridge and the information obtained from the field tests combined with a classic system identification technique provided a linear elastic updated model, accurately fitting the modal parameters of the bridge in its present condition. Hence, the use of output-only modal identification techniques and updating procedures provided a model that could be used to evaluate the overall safety of the tested bridge under the service loads.

In the practical environment, it is very common for the simultaneous occurrence of base excitation and crosswind. Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating. For this purpose, the effects of the wind speed and random excitation level are investigated with the stochastic averaging method (SAM) based on the energy envelope. The results of the analytical prediction are verified with the Monte-Carlo method (MCM). The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester (BEH) realize the performance enhancement for a weak base excitation. However, as the strength of the wind increases to a particular level, the influence of the random base excitation on the dynamic responses is weakened, and the system exhibits a periodic galloping response. A comparison between a BEH and a linear energy harvester (LEH) indicates that the BEH demonstrates inferior performance for high-speed wind. Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation. The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds. However, as the speed of the incoming wind is up to a particular level, the disadvantage of the BEH becomes clear and evident.

Adaptive modal identification of honeycomb thin-walled composite structures with pit defects under thermal modal testing using variational mode decomposition technique based on digital image correlation

In order to identify the modal parameters of time invariant three-dimensional engineering structures with damping and small nonlinearity, a novel isometric feature mapping (Isomap)-based three-dimensional operational modal analysis (OMA) method is proposed to extract nonlinear features in this paper. Using this Isomap-based OMA method, a low-dimensional embedding matrix is multiplied by a transformation matrix to obtain the original matrix. We find correspondence relationships between the low-dimensional embedding matrix and the modal coordinate response and between the transformation matrix and the modal shapes. From the low-dimensional embedding matrix, the natural frequencies can be determined using a Fourier transform and the damping ratios can be identified by the random decrement technique or natural excitation technique. The modal shapes can be estimated from the Moore–Penrose matrix inverse of the low-dimensional embedding matrix. We also discuss the effects of different parameters (i.e., number of neighbors and matrix assembly) on the results of modal parameter identification. The modal identification results from numerical simulations of the vibration response signals of a cylindrical shell under white noise excitation demonstrate that the proposed method can identify the modal shapes, natural frequencies, and ratios of three-dimensional structures in operational conditions only from the vibration response signals.

Energy generation through a hybrid energy harvester under random excitation

Modal parameters identification with environmental tests and advanced numerical analyses for masonry bell towers: a meaningful case study

Long-distance oil and gas pipelines cross complicated terrain that different section of the pipeline suffers from different seismic excitation. If a consistent ground motion input is employed to the dynamic response analysis, there will be a big difference with the actual situation. In this paper, multi-support seismic input is considered to make dynamic analysis of long-distance oil and gas pipeline, time history method is used to compare and analyze the dynamic response of a typical long-distance gas and oil pipeline with multi-support and single-support seismic excitation. The dynamic response calculating result tells that these two kinds of seismic input methods have big differences. Therefore, the effect of multi-support seismic excitation should be considered when doing earthquake response analysis of pipes.